Future Outlook of AI Agents: From Definition to Application

By 2025, AI technology has become deeply ingrained in people's lives, yet many still misunderstand the concept of an Agent. A true AI Agent project must follow the logical steps of "Perception-Thinking-Action." Taking automatic cryptocurrency investment as an example, the AI Agent first reads the latest crypto news, then assesses the impact on a particular coin, and finally makes a buy or sell decision based on the analysis results.

So, is the well-known ChatGPT considered an AI Agent? While it claims to belong to the broad category of AI Agents, if we require richer perception and execution capabilities, ChatGPT resembles more of an intelligent dialogue component. When we usually mention the term AI Agent, we actually want to emphasize two characteristics: a greater focus on solving specific problems and the ability to acquire more data from the physical world.

Based on these characteristics, we can provide a complete definition of the AI Agent:

1. Adopt the "Perception-Analysis-Action" processing flow.
2. Focus on solving specific domain problems
3. Use more data from the real world

Having understood the definition, we can explore the application prospects of AI Agents. By testing dozens of Agents across multiple frameworks, their applications can be roughly categorized into the following types:

1. AI Investment: Analyzes market trends based on real-time news and autonomously makes investment decisions.

2. AI Virtual Companion: Compared to traditional chatbots, it incorporates more personality traits and limitations.

3. Opinion Output: Provide professional commentary and analysis for specific fields.

4. Virtual idols: Digital artists created based on AI technology, capable of releasing music works and more.

5. Predictive category: AI agents specifically engaged in market prediction or event prediction.

6. AI Resource Sharing: Integrate various AI services and provide a pay-per-use model.

7. Other categories: including painting, GIF generation, music creation, and other multimodal applications.

Currently, the AI Agent field is flourishing, reminiscent of the early cryptocurrency market's prosperity. Major AI frameworks such as AI16Z, Virtual, and AVA provide developers with tools to quickly launch AI Agents, similar to the role of public chains in the crypto ecosystem. These frameworks not only offer technical support but also assist developers in issuing tokens, becoming a bridge connecting AI technology and the crypto economy.

It is worth noting that although these AI frameworks are a transformation and application of existing AI technologies to some extent, their greatest innovation may lie in the token issuance mechanism. This significantly differentiates the development process of AI Agents from traditional AI projects, enabling faster commercialization and valuation enhancement.

However, this rapid development has also brought about the risk of a bubble. Currently, the market is highly enthusiastic about AI Agent projects, and if there were a fear and greed index, the greed index might be close to or exceed 90.

Although some question the technical value of these projects, I believe one of the best use cases for cryptocurrency is to accelerate the process of market discovery. In this intense environment of survival of the fittest, excellent products and teams can quickly gain recognition and support, while inferior projects are swiftly rejected by the market.

This environment may be able to incubate unexpected innovative products in the traditional AI field. As time goes by, the continuous advancement of AI technology may bring more astonishing applications. We look forward to the future development of the AI Agent field, just as discussed in "Blade Runner"; perhaps one day we will ponder profound questions like "Do androids dream of electric sheep?".